Datasets composed of time-to-event, within-subject clustered observations are common in patient oriented dental research, and e.g. caries data are recorded from multiple teeth or even multiple surfaces per tooth from each patient. The analysis of data composed of multiple observations per patient is a challenging, yet often overlooked, proposition. Most routinely used statistical analysis procedures require the common assumption that all observations are independent. In the presence of clustered observations, these procedures are usually not directly applicable. To make valid inferences, more sophisticated statistical tools are needed in order to take within cluster correlations into account. The application of sophisticated survival method analyses in patient-oriented dental research is limited. To address this deficiency, Dr. Chuang (principal investigator) is submitting a R03 award to fund his special interests and skills in the quantitative analyses of patient-oriented dental research. This award's broad goal is to facilitate the principal investigator to develop sound and rigorous survival analytic methods with applications in dental research and in the future to function as an independent patient-oriented dental researcher, mentor and clinician. Dr. Chuang's environment is outstanding for implementing patient-oriented research. The department and institution is committed to provide individuals in patient-oriented research methods. The R03 award will provide funding for protected time with at least 35% research effort. The first specific aim of this R03 award is to identify exposures associated with implant failures and complications with a generalized linear transformation model via the marginal approach. The second specific aim is to identify exposures associated with implant failures and complications with a generalized linear transformation model via the frailty approach and to compare and contrast these two [unreadable] different approaches. The principal investigator has chosen this research experience because of its clinical relevance and challenging methodological and analytic issues. The analyses focus on the survival methodological issues of correlated or clustered observations with applications to dental research. The specific analytic issues addressed are generalizable to patient-oriented dental research as many studies using multiple, correlated observations per patient, i.e. probing depths, tooth loss. [unreadable] [unreadable] [unreadable]